pysoftk.pol_analysis package

Subpackages

• pysoftk.pol_analysis.tools package
  • Submodules
  • pysoftk.pol_analysis.tools.clustering_prob_distribution_plot module
    • total_number_clusters()
  • pysoftk.pol_analysis.tools.utils_mda module
    • MDA_input
      • MDA_input.xtc
      • MDA_input.tpr
      • MDA_input.get_mda_universe()
  • pysoftk.pol_analysis.tools.utils_tools module
    • coord_matrix_calc()
    • create_binned_space()
    • create_network()
    • distance_matrix_calc()
    • find_values()
    • get_atom_name_list()
    • get_frames()
    • get_frames_hydr()
    • get_index_pairs()
    • get_universe_per_frame()
    • pair()
    • selecting_atoms()
    • selecting_atoms_density()
  • pysoftk.pol_analysis.tools.utils_tools_old module
    • coord_matrix_calc()
    • create_network()
    • distance_matrix_calc()
    • find_values()
    • get_atom_name_list()
    • get_frames()
    • get_frames_hydr()
    • get_index_pairs()
    • get_universe_per_frame()
    • pair()
    • selecting_atoms()
  • Module contents

Submodules

pysoftk.pol_analysis.clustering module

class pysoftk.pol_analysis.clustering.SCP(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute a spatial cluster for polymers (SCP)

contact_matrix(u, name_list, cluster_cutoff)

Function to compute the contact matrix.

Parameters:

• u (MDAnalaysis.Universe) – An user-provided MDAnalysis universe.

• name_list (class.list) – A list containing the names used for the contact matrix analysis.

• cluster_cutoff (class.float) – A user-defined number for a radius cutoff.

Returns:

pairs – A list of tuples containing the indexes of the selected molecules.

Return type:

class.list

spatial_clustering(u, atom_sel, cluster_cutoff, frame)

Function that gives you the resids and sized of each polymer aggregate per frame in a trajectory.

Parameters:

• frame (MDanalysis.Object) – An MDAnalysis object that contains one frame of a trajectory.

• atom_sel (class.str) – User-provided string containing the ResID/tag of the molecule in the trajectory.

• cluster_cutoff (class.int) – User defined cutoff to select as neighbour.

• max_workers (class.int) – Number of threads to be used in the calculation.

Returns:

• tuple containing clusters and cluster_sizes.

• clusters (class.list) – A tuple containing the ResIDs.

• cluster_sizes (class.list) – Length of the computed clusters.

spatial_clustering_run(start, stop, skip, atom_names, cluster_cutoff, name_file)

Function to compute the spatial clustering function over an MDAnalysis

trajectory.

Parameters:

• start (class.int) – Frame to start calculation.

• stop (class.int) – Frame to stop calculation.

• step (class.int) – Number of frames to skip.

• atom_names (class.str) – Atomic names used to procure the search.

• cluster_cutoff (class.float) – User-provided value to define the cluster length.

• name_file (class.str) – Name of the User-supplied file.

Returns:

A pandas.DataFrame.parquet file with the results stored.

Return type:

None

pysoftk.pol_analysis.clustering.timeit(func)

pysoftk.pol_analysis.contact_analysis module

class pysoftk.pol_analysis.contact_analysis.contacts(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute the contacts between the polymers of a micelle.

contacts_calc(u, micelle_selection, micelle_positions, group1, group2, contact_distance)

Function to get atom pairs

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDanalysis trajectory.

• micelle_selection (MDAnalysis.Object) – MDAnalysis atom group of atoms belonging to the micelle

• micelle_positions (np.array) – positions of all atoms from micelle selection

• group1 (class.str) – atom names of the atoms for group1 of the contacts calculation

• group2 (class.str) – atom names of the atoms for group2 of the contacts calculation

Returns:

contacts_mat – Array with the contacts between polymers

Return type:

np.array

run_contacts_calc(micelle_selection, micelle_positions, group1, group2, contacts_distance)

Function to run contacts_calc function over timme

Parameters:

• micelle_selection (class.list) – List with resids of the polymers belonging to the micelle

• micelle_positions (np.array) – Array with the positions of all atoms of the micelle

• group1 (class.str) – Atom names of the atoms for group1 of the contacts calculation

• group2 (class.str) – Atom names of the atoms for group2 of the contacts calculation

• contacts_distance (class.int) – Cut off distance for contacts

Returns:

contacts_over time – Array with the contacts between polymers in each timestep

Return type:

np.array

pysoftk.pol_analysis.contact_analysis.timeit(func)

pysoftk.pol_analysis.ecc_micelle module

class pysoftk.pol_analysis.ecc_micelle.ecc(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute the eccentricity of micelles

ecc_calc(atom_sel_micelle, micelle_positions)

Function to calculate the eccentricity of the chosen atoms

Parameters:

atom_sel_micelle (MDAnalysis.Object) – MDAnalysis.atom_selection function

micelle_positionsnp.array

np.array with the positions of the micelle atoms

Returns:

ecc – Eccentricity of the selected atoms

Return type:

class.float

running_ecc(atom_names, micelle_positions, start, stop, skip)

Function to calculate the eccentricity of the chosen atoms over time

Parameters:

• atom_sel_type (class.str) – Type of atom selection

• atom_names (class.list) – List with the names of atoms

• micelle_positions (np.array) – np.array with the positions of the micelle atoms

• Start (class.int) – Starting frame of the trajectory

• Stop (class.int) – Ending rame of the trajectory

• Skip (class.int) – Skipping every that many framesof the trajectory

Returns:

ecc – Eccentricity of the selected atoms over time

Return type:

np.array

pysoftk.pol_analysis.intrinsic_density_micelle module

class pysoftk.pol_analysis.intrinsic_density_micelle.intrinsic_density(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute the contacts between the polymers of a micelle.

box_volume(u, frame)

Function to calculate the volume of the system box at a specific frame

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDanalysis trajectory.

• frame (int) – frame selected for volume calculation

Returns:

vol – volume of system box

Return type:

float

intrinsic_density_not_normalized(u, frame, whole_micelle_largest_cluster_resids, micelle_selection, micelle_positions, core_group, shell_group, n_rand_points, n_bins, n_min, n_max, n_step)

Function to run the intrinsic density in a specific frame

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDanalysis trajectory.

• whole_micelle_largest_cluster_resids (list) – list with resids of polymers forming the desired micelle

• micelle_selection (MDAnalysis.Object) – MDAnalysis atom group of atoms belonging to the micelle

• micelle_positions (np.array) –

  positions of all atoms from micelle selection

  core_groupclass.str

  atom names of the atoms of the core for density calculation

• shell_group (class.str) –

  atom names of the atoms of the shell for density calculation

  n_rand_pointsint

  number of water molecules

  n_binsint

  nnumber of bins for the density calculation

  n_minint

  min bin value for density calculation

  n_maxint

  max bins value for density calculation

  n_stepint

  size of bin

Returns:

• intrinsic_r_total (np.array) – not normalized intrinsic density

• intrinsic_r_total_norm (np.array) – normalized intrinsic density

run_intrinsic_density(micelle_selection, micelle_positions, core, shell, water_name, start, stop, step, n_bins=31, n_min=-40.5, n_max=150, n_step=0.1)

Function to run the intrinsic density over time

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDanalysis trajectory.

• micelle_selection (MDAnalysis.Object) – MDAnalysis atom group of atoms belonging to the micelle

• micelle_positions (np.array) –

  positions of all atoms from micelle selection

  coreclass.str

  atom names of the atoms of the core for density calculation

• shell (class.str) –

  atom names of the atoms of the shell for density calculation

  water_nameclass.str

  name of water atoms

  startint

  starting frame to perform calculation

  stopint

  last frame to perform calculation

  stepint

  frames skipped in calculation

  n_binsint

  nnumber of bins for the density calculation

  n_minint

  min bin value for density calculation

  n_maxint

  max bins value for density calculation

  n_stepint

  size of bin

Returns:

final_density – intrinsic density

binned_space : np.array array with the values of the binned radial distance, this allows easier plotting of the density

Return type:

np.array

pysoftk.pol_analysis.intrinsic_density_micelle.timeit(func)

pysoftk.pol_analysis.intrinsic_density_water_micelle module

class pysoftk.pol_analysis.intrinsic_density_water_micelle.intrinsic_density_water(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute the contacts between the polymers of a micelle.

box_volume(u, frame)

Function to calculate the volume of the system box at a specific frame

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDanalysis trajectory.

• frame (int) – frame selected for volume calculation

Returns:

vol – volume of system box

Return type:

float

intrinsic_density_not_normalized(u, frame, whole_micelle_largest_cluster_resids, micelle_positions, water_selection, core_group, n_rand_points, n_bins, n_min, n_max, n_step)

Function to run the intrinsic density in a specific frame

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDanalysis trajectory.

• frame (int) – trajectory frame

• whole_micelle_largest_cluster_resids (list) – list with resids of polymers forming the desired micelle

micelle_positionsnp.array

positions of all atoms from micelle selection

water_selection: list

list of solvent atoms to calculate the density

core_groupclass.str

atom names of the atoms of the core for density calculation

n_rand_pointsint

number of water molecules

n_binsint

nnumber of bins for the density calculation

n_minint

min bin value for density calculation

n_maxint

max bins value for density calculation

n_stepint

size of bin

Returns:

• intrinsic_r_total (np.array) – not normalized intrinsic density

• intrinsic_r_total_norm (np.array) – normalized intrinsic density

run_intrinsic_density(micelle_selection, micelle_positions, water_selection, core, heavy_atom_water_name, start, stop, step, n_bins=31, n_min=-40.5, n_max=150, n_step=0.1)

Function to run the intrinsic density over time

Parameters:

• micelle_selection (list) – list of atoms belonging to the micelle

• micelle_positions (np.array) –

  positions of all atoms from micelle selection

  water_selectionlist

  solvent atom selection

  coreclass.str

  atom names of the atoms of the core for density calculation

• shell (class.str) –

  atom names of the atoms of the shell for density calculation

  heavy_atom_water_nameclass.str

  name of heavy water atoms

  startint

  starting frame to perform calculation

  stopint

  last frame to perform calculation

  stepint

  frames skipped in calculation

  n_binsint

  nnumber of bins for the density calculation

  n_minint

  min bin value for density calculation

  n_maxint

  max bins value for density calculation

  n_stepint

  size of bin

Returns:

final_density – intrinsic density

binned_space : np.array array with the values of the binned radial distance, this allows easier plotting of the density

Return type:

np.array

select_water_atoms(u, name)

Function to select the solvent atoms

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDanalysis trajectory

• name (list) – List with the atom names of the solvent

pysoftk.pol_analysis.intrinsic_density_water_micelle.timeit(func)

pysoftk.pol_analysis.make_micelle_whole module

class pysoftk.pol_analysis.make_micelle_whole.micelle_whole(tpr_file, xtc_file)

Bases: MDA_input

A class used to make the largest micelle whole across the pbc for better analysis.

count_dimensions(box, cluster_atoms_positions, dimensions)

Function to get the dimensions of a system, the box size and cluster_atom_positions in the form to use in make_cluster_whole

Parameters:

• box (np.array) – u.dimensions

• cluster_atom_positions (np.array) – Array with the atom positions of the polymers belonging to the cluster

• dimensions (class.int) – Number of dimensions

Returns:

• box (np.array) – Array with the u.dimensions to feed in into make_cluster_whole

• cluster_atom_positions (np.array) – Array with the atom positions of the micelle/cluster in the correct shape to feed it into make_cluster_whole

• dimensions (class.list) – List with the number of dimensions. E.g. 3D=[0, 1, 2]

get_atom_name_list(atom_sel)

Function to obtain the residues based on user-provided atom selection.

Parameters:

atom_sel (class.str) – User Provided name/tag of the molecules inside the box.

Returns:

final – List containing all names of atoms.

Return type:

class.list

get_polymer_positions(u, frame, resname, cluster_resids)

Function to find the polymer positions

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDAnalysis universe.

• frame (class.int) – Time frame for calculation to be done.

• resname (class.list) – List of strings with the resname of the polymers.

• cluster_resids (class.str or class.int) – List with the polymer resids.

Returns:

• box (np.array) – Array with the u.dimensions

• cluster_atom_positions (np.array) – Array with the atom positions of the micelle/cluster.

• cluster_sel (np.array) – Array with the atoms that belong to the micelle/cluster.

make_cluster_whole(frame, resname, cluster_resids, bins_min, bins_max, bins_step, dimensions=3)

Function to make a polymer cluster whole across the pbc

Parameters:

• frame (class.int) – Time frame that wants to be made whole

• resname (class.list) – List with the resname of the molecules of the cluster

• cluster_resids (class.list) – List with resids of the polymers that want to be made whole

• bins_min (class.int) – Smallest distance to evaluate if the pbc are broken (smallest x-y distance position)

• bins_max (class.int) – Biggest distance to evaluate if the pbc are broken (largest x-y distance position)

• bins_step (class.int) – Step between bins to evaluate broken pbc

Returns:

• frame (class.int) – Time frame where the micelle has been made whole

• atom_positions_whole (np.array) – Array with the atom positions of the micelle made whole across the pbc

obtain_largest_micelle_resids(spatial_clustering_results)

Function to obtain the largest micelle resids Bare in mind this may give two different clusters if they have the same size - should check that you only select one when using the results from here

Note-need to check if it actually gives two different clusters if they have the same size.

Parameters:

spatial_clustering_results (pandas.DataFrame) – Results from clustering analysis class. Pandas dataframe with three columns: time (ps), micelle_resids and micelle_size

Returns:

longest_lists – list with the number resids (of MDanalysis) of the largets micelle at the timesteps that want to be evaluated.

Return type:

list

obtain_snapshot(output_name, atom_positions_at_specific_frame, cluster_resids, polymer_resname, frame, water_resname=['SOL'], water_atom_name=['OW'], solvant=False)

Function to obtain an snapshot of the micelle (pdb) file of a specific frame and returns the new universe to analyse.

Parameters:

• output_name (class.str) – Name of output file

• atom_positions_at_specific_frame (np.array) – Position of atoms at a specific frame

• cluster_resids (class.list) – List of polymers resids for the snapshot

• frame (class.int) – Time frame for snapshot

• water_resname (class.list) – List with name of solvants

• water_atom_name (class.list) – List of solvant atom names that want to be outputed in the sanpshot. E.g. with water you may only be interested in outputing the oxygen water atom for further calculations

• solvant (class.boolean) – Set to True if interested in obtainig an output snapshot with the solvant too.

Returns:

• u3 (MDAnalysis.Universe) – An MDAnalysis universe containing the resulting frames

• output (MDAnalysis.Write) – A PDB file containing the selected molecules.

pbc_per_dimension(cluster_sel_positions, box, dimension, bins_min, bins_max, bins_step)

Function to find the broken parts of the micelle across the pbc and make it whole

Parameters:

• spatial_clustering_results (np.array) – Numpy array with the positions of the resids of interest. It needs to have the shape of n_molec x 3

• box (np.array) – Numpy array with the MDanalysis strat u.dimensions. Array with the x y and z dimensions follow by the angles of the box.

• dimension (class.int) – Dimension number that wants to be evaluated

• bins_min (class.int) – Smallest distance to evaluate if the pbc are broken (smallest x-y distance position)

• bins_max (class.int) – Biggest distance to evaluate if the pbc are broken (largest x-y distance position)

• bins_step (class.int) – Step between bins to evaluate broken pbc

Returns:

cluster_sel_positions_return – Array with the atom positions of the micelle made whole across the pbc

Return type:

np.array

running_make_cluster_whole(resname, cluster_resids, start, stop, skip, bins_min=-50, bins_max=50, bins_step=10)

Function to run the make_cluster_whole function over several frames

Parameters:

• resname (class.list) – List with the resname of the molecules of the cluster in each time step.

• cluster_resids (class.list) – List with resids of the polymers that want to be made whole in each time step.

• start (class.int) – Starting frame to perfomr the calculation.

• stop (class.int) – Last frame to perform the calculation.

• skip (class.int) – Length of step to perform the calculation every number of frames.

• bins_min (class.int) – Smallest distance to evaluate if the pbc are broken (smallest x-y distance position).

• bins_max (class.int) – Biggest distance to evaluate if the pbc are broken (largest x-y distance position).

• bins_step (class.int) – Step between bins to evaluate broken pbc.

Returns:

atom_positions_over_trajectory – List of np.arrays where each entry of the list is the position of atoms that are made whole across the pbc at a specific time step.

Return type:

class.list

pysoftk.pol_analysis.make_micelle_whole.timeit(func)

pysoftk.pol_analysis.rgyr_micelle module

class pysoftk.pol_analysis.rgyr_micelle.rgyr(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute the radius of gyration of micelles

rgyr_calc(atom_sel_micelle, micelle_positions, subgroup=[])

Funcion to calculate the radius of gyration of the chosen atoms

Parameters:

• atom_sel_micelle (MDAnalysis.atom_selection) – MDAnalysis atom_selection function.

• subgroup (MDAnalysis.atom_group) – MDAnalysis atom group to calculate the rgyr

• micelle_positions (np.array) – np.array with the positions of the micelle atoms

Returns:

radius_of_gyration – Radius of gyration of the selected atoms

Return type:

class.float

running_rgyr(atom_names, micelle_positions, start, stop, skip, subgroup=[])

Function to calculate the radius of gyration of the chosen atoms.

Parameters:

• u (MDAnalysis.Universe) – An user-provided MDAnalysis universe.

• atom_sel_type (class.str) – Type of atom selection.

• atom_names (class.list) – List with the names of atoms.

• micelle_positions (np.array) – An array with the positions of the micelle atoms.

• subgroup (class.str) – A list of atom names to calculate the rgyr.

• Start (class.int) – Starting frame of the trajectory.

• Stop (class.int) – Ending rame of the trajectory.

• Skip (class.int) – Skipping every that many frames of the trajectory.

Returns:

rgyr_f – Radius of gyration of the selected atoms over time

Return type:

np.array

pysoftk.pol_analysis.rgyr_micelle.timeit(func)

pysoftk.pol_analysis.ring_ring module

class pysoftk.pol_analysis.ring_ring.RSA(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute a Ring Stacking Analysis (RSA).

GetRingSystems(min_1, max_1, min_2, max_2, includeSpiro=False)

Function to detect the atomic indexes that belong to a ring structure for a provided molecular complex (single, dimer, timer and so on molecules).

Parameters:

• min_1 (int) – smallest atom index of molecule 1

• max_1 (int) – largest atom index of molecule 1

• min_2 (int) – smallest atom index of molecule 2

• max_2 (int) – largest atom index of molecule 2

• includeSpiro (class.bool) – To check for spiro sites

Returns:

ring_contact_indices – A list of arrays with the mda atom indices of the rings of the polymers.

Return type:

class.list

calc_angle(u_norm, u_norm2)

Function to compute the dot product between two normal

vectors.

Parameters:

• u_norm (numpy.ndarray) – An user-provided normal vector.

• u_norm2 (numpy.ndarray) – An user-provided normal vector.

Returns:

Result of a dot product between two vectors.

Return type:

None

find_several_rings_stacked(rings_df_name)

Function to find several rings stacked using a provided

pandas DataFrame from previous calculations.

Parameters:

rings_df_name (pandas.DataFrame) – Pandas dataframe containing the results from the ring_ring analysis.

Returns:

connected_components – List of connected polymers along the trajectory.

Return type:

class.list

get_polymer_resids(pol_indices)

Function to get the possible ring combinations between two polymers to calculate the distances between them.

Parameters:

pol_indices (np.array) – Numpy array with the atom indices of the dimer.

Returns:

ring_comb – A list of arrays with the combination of mda molecule resids of the two molecules involved

Return type:

class.list

nearest_neighbours(u, lab1, lab2)

Function to filter different molecules

by closest interatomic distance.

Parameters:

• u (MDAnalysis.object) – Universe containing the trajectory

• lab1 (str) – User provided label of one molecule

• lab2 (str) – User provided label for second molecule

• frame (int) – Frame for calculation

Returns:

float – Minimum distance between the atoms belonging to the polymer pair and all the atompositions.

Return type:

np.float

number_pol(u)

Number of polymers inside an user-provided box.

Parameters:

u (MDAnalysis.Universe) – An user-provided MDAnalysis universe.

Returns:

Number of polymers within a box.

Return type:

None

pol_cutoff(u, cutoff)

Function to count the number of polymers within an

user-provided cutoff.

Parameters:

• u (MDAnalysis.universe) – An user-provided universe of MDAnalysis

• cutoff (float) – An user provided cutoff defining closest distances.

• frames (list) – User provided frames where calculation will be carried out

Returns:

index_cutoff – List of intergers with the indexes of the selected

molecules.

b: list

List of possible combinations of the selected molecules

Return type:

list

rings_stacking_dist(u, ring_comb, polymer_pos_1, polymer_pos_2, pol_indices, cut_off_stack=5, par_scheme='OpenMP')

Function to find if two rings are stacked. This is done by checking if the distance of geometry between two rings is smaller than an user-defined cut off distance.

Parameters:

• ring_comb (numpy.ndarray) – Numpy array with all possible ring combinations

• polymer_pos_1 (numpy.ndarray) – Numpy array with the correct positions of all atoms of the polymer.

• polymer_pos_2 (numpy.ndarray) – Numpy array with the correct positions of all atoms of the polymer.

• pol_indices (numpy.ndarray) – Numpy array with the first atom index of each polymer. The first one needs to be the one corresponding to polymer_pos_1 and the second one to polymer_pos_2

• cut_off_stack (class.float) – Cut off distance for ring stackings

Returns:

vector_angle – Angle between the two planes of atoms

Return type:

class.float or class.boolean

run_rings_stacking_dist(u_frame, ring_comb, cut_off, ang_cutoff)

Function to find if two rings are stacked. This is done by checking if the distance of geometry between two rings is smaller than a user-defined cut off distance.

Parameters:

• u_frame (int) – time step of the calculation

• ring_comb (numpy.ndarray) – Numpy array with all possible ring combinations

• cutoff (class.float) – Cut off distance for ring stackings

• ang_cut_off (class.float) – Cut off angle for ring stackings

Returns:

• ring_contact_atoms (class.list) – A list of arrays with the mda atom indices of the rings of the polymers

• pol_idx (class.list) – A list of the resids of the molecules with ring stacking

separate_rings(ring_contact_indices, pol2_min)

Function to get the possible ring combinations between two polymers to calculate the distances between them.

Parameters:

• ring_contact_indices (class.list) – A list of arrays with the mda atom indices of the rings of the polymers.

• pol2_min (int) – smallest atom index of the molecule with largest atom index

Returns:

ring_comb – A list of arrays with the mda atom indices of the rings of the polymers in contact.

Return type:

class.list

stacking_analysis(cut_off, ang_cut, start, stop, step, output_name='output.parquet')

Function to perform a stacking analysis over several frames :param u: An user-provided universe of MDAnalysis :type u: MDAnalysis.universe :param cutoff: An user provided cutoff defining closest distances. :type cutoff: float :param ang_cut: An user provided cutoff defining the valid ring stacking angle range. :type ang_cut: float :param start: starting frame to perform the ring analysis. :type start: int :param stop: stopping frame of the ring analysis. :type stop: int :param step: number of frames to skip during the ring analysis. :type step: int :param output_name: name of output parquet file with the ring analysis. :type output_name: nstr

Returns:

pandas dataframe with atom indexes of rings where there is ring stacking at each time frame.

Return type:

None

svd(coordinates)

Function to obtain the Single Value Decomposition (SVD)

of coordinates.

Parameters:

coordinates (numpy.ndarray) – Array containing the coordinates upon which svd is going to be calculated.

Returns:

vh – A numpy.ndarray with the right unitary singular vector, orthogonal to the given set of coordinates.

Return type:

numpy.ndarray

pysoftk.pol_analysis.ring_ring.timeit(func)

pysoftk.pol_analysis.solvation module

class pysoftk.pol_analysis.solvation.solvation(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute the contacts between the polymers of a micelle

hydration_calc(frame, largest_cluster_resids, micelle_pos, water_name, polymer_oxygen_names, cut_off)

Function to calculate the solvation of selected polymer atoms

Parameters:

• frame (class.int) – Time frame of step for calculation.

• largest_cluster_resids (class.list) – List with resids of polymers forming the micelle at a specific time step.

• micelle_pos (np.array) – 3D np.array with the positions of the atoms that conform the micelle whole (not broken across the pbc boundaries).

• water_name (class.str) – Water atom names for hydration calculation.

• polymer_oxygen_names (class.list) – List of atom names of the polymer for hydration calculation.

• cut_off (class.float) – Number cut off of the distance between the polymer beads and the water for hydration calculation.

Returns:

coord_number – Coordination number of the polymer atoms.

Return type:

list

solvation_calc_run(start_frame, stop_frame, step_frame, largest_cluster_resids, micelle_pos, water_name, polymer_oxygen_names, cut_off)

Function to calculate the solvation calculation over the selected frames

Parameters:

• start_frame (class.int) – frame to start calculation

• stop_frame (class.int) – frame to stop calculation

• step_frame (class.int) – number of frames to skip

• largest_cluster_resids (class.list) – list with resids of polymers forming the micelle at a specific time step

• micelle_pos (np.array) – 3D np.array with the positions of the atoms that conform the micelle whole (not broken across the pbc boundaries)

• water_name (class.str) – warer atom names for hydration calculation

• polymer_oxygen_names (class.list) – list of atom names of the polymer for hydration calculation

• cut_off (class.float) – number cut off of the distance between the polymer beads and the water for hydration calculation.

Returns:

coord_number – coordination number of the polymer atoms at a specific frame

Return type:

class.list

pysoftk.pol_analysis.solvation.timeit(func)

pysoftk.pol_analysis.spherical_density module

class pysoftk.pol_analysis.spherical_density.spherical_density(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute the contacts between the polymers of a micelle.

density_calc(binned_space, all_histograms)

Function to calculate the density

Parameters:

binned_space (np.array) – bins

all_histogramsnp.array

distances histograms

Returns:

density – array with density

Return type:

np.array

dist_com(u, atom_sel_micelle, micelle_positions, atom_selection)

Function to calculate the distance between atoms and the center of mass of the micelle

Parameters:

• u (mda.Universe) – mda.Universe

• atom_sel_micelle –

  atom group selection of the micelle

  micelle_positionsnp.array

  array with the positions of the micelle whole

Returns:

distance_com – array with the distances of the aotms to the COM of the micelle

Return type:

np.array

run_density_calc(micelle_sel_type, whole_micelle_selection, micelle_positions, group_atom_selection, maxbin=200, minbin=0, step=0.1)

Function to get the mean density calculation over time as a funciton wrt the micelle COM

Parameters:

• micelle_sel_type (str) – string type for the selection of the micelle atoms

• whole_micelle_selection (np.array) – elements to select the micelle atoms

• micelle_positions (np.array) – array with the positions of the micelle atoms whole

• group_atom_selection (str) – list with the names of the polymer species chosen for the density calculation

• maxbin (int) – largest bin value

• minbin (int) – smalles bin value

• step (int) – bin size

Returns:

density – array with the density values as a function of the distance to the COM of the micelle

binned_spacenp.array

array with the values of the binned radial distance, this allows easier plotting of the density

Return type:

np.array

sph_histogram(distance, maxbin, minbin, step)

Function to create a histogram of the distances

Parameters:

• distance (np.array) – distances to be binned

• maxbin (int) – largest bin value

• minbin (int) – smalles bin value

• step (int) – bin size

Returns:

all_histograms – array with the distances values binned

Return type:

np.array

pysoftk.pol_analysis.spherical_density.timeit(func)

pysoftk.pol_analysis.spherical_density_water module

class pysoftk.pol_analysis.spherical_density_water.spherical_density_water(tpr_file, xtc_file)

Bases: MDA_input

A class used to compute the contacts between the polymers of a micelle.

density_calc(binned_space, all_histograms)

Function to calculate the density

Parameters:

binned_space (np.array) – bins

all_histogramsnp.array

distances histograms

Returns:

density – array with density

Return type:

np.array

dist_com(u, frame, atom_sel_micelle, micelle_positions, water_selection)

Function to calculate the distance between atoms and the center of mass of the micelle

Parameters:

• u (mda.Universe) – mda.Universe

• atom_sel_micelle –

  atom group selection of the micelle

  micelle_positionsnp.array

  array with the positions of the micelle whole

Returns:

distance_com – array with the distances of the aotms to the COM of the micelle

Return type:

np.array

run_density_calc(micelle_sel_type, whole_micelle_selection, micelle_positions, water_sel_type, water_atom_selection, start, stop, step_frame, maxbin=200, minbin=0, step=0.1)

Function to get the mean density calculation over time as a funciton wrt the micelle COM

Parameters:

• micelle_sel_type (str) – string type for the selection of the micelle atoms

• whole_micelle_selection (np.array) – elements to select the micelle atoms

• micelle_positions (np.array) – array with the positions of the micelle atoms whole

• water_sel_type (str) – string type for the selection of the solvent atoms

• water_atom_selection (list) – list with the names of the solvent chosen for the density calculation

• maxbin (int) – largest bin value

• minbin (int) – smalles bin value

• step (int) – bin size

Returns:

density – array with the density values as a function of the distance to the COM of the micelle

binned_spacenp.array

array with the values of the binned radial distance, this allows easier plotting of the density

Return type:

np.array

sph_histogram(distance, maxbin, minbin, step)

Function to create a histogram of the distances

Parameters:

• distance (np.array) – distances to be binned

• maxbin (int) – largest bin value

• minbin (int) – smalles bin value

• step (int) – bin size

Returns:

all_histograms – array with the distances values binned

Return type:

np.array

pysoftk.pol_analysis.spherical_density_water.timeit(func)

pysoftk.pol_analysis.umap_analysis module

pysoftk.pol_analysis.umap_analysis.timeit(func)

class pysoftk.pol_analysis.umap_analysis.umap_analysis(all_pos)

Bases: object

A class used to compute to do umap cluster identification of polymer conformations within an spatial configuration of moieties.

cluster_order_appearance(X_embedded, y_pred, cwd)

Function to ouput hdbscan with the groups labeled ordered

with their order of appearance in the trajectory.

Parameters:

• X_embedded (np.array) – umap clustered data

• y_pred (np.array) – cluster label assignment for each data point in the umap cluster data.

• cwd (class.str) – path to save output file.

Returns:

A plot with the results of the calculation.

Return type:

None

find_closest_point(array, target_point)

Function to find the closest point from an array to a given target point

Parameters:

• array (np.array) – array of numbers from which the value will be found

• target_point (class.float) – target number

Returns:

closest_point – numpy array with the closest number from array to the target point.

Return type:

np.array

get_array()

Function to load the all pos distances.

Parameters:

None

Returns:

all_pos – np.array to load

Return type:

np.array

get_average_rep_cluster(X_embedded, y_pred)

Function to get the X_embedded point that represents the

mean of each umap cluster.

Parameters:

• X_embedded (np.array) – umap clustered data

• y_pred (np.array) – cluster label assignment for each data point in the umap cluster data.

• cwd (class.str) – path to save output file.

Returns:

cluster_points – np.array with the X_embedded values that represent the mean of each cluster.

Return type:

np.array

hdbscan_cluster(X_embedded, min_cs, epsilon, cwd, method='leaf')

Function to hdbscan on umap clustered data.

Parameters:

• X_embedded (np.array) – umap clustered data

• min_cs (class.int) – minimum number of points for a group to be considered a cluster.

• epsilon (class.int) – clusters closer than this distance apart will be merged.

• cwd (class.str) – path to save output file.

• method (class.str) – cluster_method_selection from hdbscan to determine how it selects flat clusters from the cluster tree hierarchy.

Returns:

y_pred – cluster label assignment for each data point in the umap cluster data.

Return type:

np.array

umap_run(n_neigh, cwd, n_comp=2, min_d=0.0, verb=True, rs=9)

Function to run umap on all_pos array.

Parameters:

• n_neigh (class.int) – larger numbers forcus more on global properties (and increase computational effort required)

• cwd (class.str) – path to save output file

• n_comp (class.int) – set the number of dimensions to reduce to

• min_d (class.int) – must be 0.0 if points are to be clustered later with HDBSCAN.

• verb (class.boolean) – To show the progress bar

• rs (class.int) – random seed. Must be set to the same number for reproducibility.

Returns:

X_embedded – Clustered data

Return type:

np.array

Module contents